基于人工鱼群的中继卫星多用户检测方法

随着航天技术的发展,未来的中继卫星系统需要为多个用户航天器提供码分多址通信服务。因此需要采用多用户检测技术来抑制多个用户航天器信号之间的多址干扰。文中将人工鱼群优化算法引入到中继卫星系统多用户检测中,通过模拟人工鱼群觅食过程中的觅食行为、聚集行为以及尾随行为,利用人工鱼群的迭代优化,实现多址干扰的最小化。为加快人工鱼群算法的收敛速度,文中将解相关多用户检测的结果作为人工鱼群算法的迭代初值。结果表明,基于人工鱼群算法的多用户检测方法误码率在信噪比为10 dB时可以达到10 ^-6数量级,在误码率、远近效应以及用户容量等方面的性能优于传统的多用户检测方法。

Artificial Fish Swarm Algorithm Based on Multiuser Detection for Data Relay Satellite System

With the development of space technology, future relay satellite systems need to provide code division multiple access communication services for multiple user spacecraft. Therefore, multi-user detection techniques were employed to suppress the multiple access interference. In this paper, the artificial fish swarm algorithm was introduced into the multi-user detection of the relay satellite system. By simulating the preying behavior, swarming behavior and following behavior of artificial fishes, the multiple access interference was minimized iteratively. In order to speed up the convergence speed of the artificial fish swarm algorithm, the results of decorrelating multiuser detection were employed as initial values of the artificial fishes. The results showed that the bit error rate of the artificial fish swarm algorithm based multiuser detection method could approach 10 ^-6 at the SNR of 10 dB, and its performance was better than traditional multi-user detection method in terms of bit error rate, near-far effect and user capacity.